Neo4j Staff Predictions for 2020

A new year (let alone a new decade) is always a great time to reflect on the year gone past but also where we’re headed. We leaned on some of our most forward-thinking Neo4j colleagues – Amy Hodler, Michael Hunger… Read more →

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The Top 7 Neo4j Videos of 2019

In lieu of our bi-weekly #GraphCast, we thought we would share some of the best Neo4j videos from 2019. Consider this an almost-New Year’s Eve celebration of all things video. (No order or favorites here. Just cool videos in a… Read more →

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The Top 5 Neo4j Podcasts of 2019

Catch up with all of the best episodes from the Neo4j Graphistania podcast during 2019, including episodes with the rebooted format and new co-host.

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Graphs on GPUs: 5-Minute Interview with Saul Rosales

In this week’s five-minute interview (conducted at GraphTour DC 2019), we discuss how Saul Rosales and his team use Neo4j with Graphistry.

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Responsible AI: The Critical Need for Context (and Practical Tips)

Read the second and final installment of this blog series on responisble AI, why context is critical to achieving responsible AI, and get practical tips.

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A Conversation with Graphs

Editor’s Note: This presentation was given by Tatiana Hartinger at GraphConnect New York in September 2018. Presentation Summary Tatiana Hartinger is a mathematician and a Cognitive Solutions Consultant specializing in graph theory from Cognitiva. Cognitiva is using graphs to enhance… Read more →

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Reveal Hidden Patterns In Healthcare Data: Graph Analytics and the Opioid Crisis

Read this blog series to discover leading-edge graph analytic techniques to derive intelligence from complex healthcare data.

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Real Examples of Why We Need Context for Responsible AI

Read part one of this two-part series on responsible AI. Discover real-world examples of the myths,., biases and more that currently surround AI.

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How Boston Scientific Improves Manufacturing Quality Using Graph Analytics

Editor’s Note: This presentation was given by Eric Wespi and Eric Spiegelberg at GraphConnect New York in September 2018. Presentation Summary We’re going to talk about some project themes that make sense when you’re going about developing a graph project.… Read more →

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Live from Lyft: Q&A with Mark Grover, Product Manager at Lyft

Discover how Lyft has integrated Neo4j into their data sharing process and how they test information integrity with Amundsen.

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How Graphs Enhance Artificial Intelligence

Explore the increasing impact of graph technology on artificial intelligence and the steps toward enhancing AI and ML with a graph database.

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DeepWalk: Implementing Graph Embeddings in Neo4j

Discover tips and strategies for implementing graph embedding into a Neo4j graph database, with plenty of Cypher examples.

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AI & Graph Technology: AI Explainability

Read the fifth and final installment of our blog series on artificial intelligence and the ways AI explainability adds context for credibility.

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AI & Graph Technology: Connections Improve Accuracy

Read the fourth installment of this blog series on artificial intelligence on the ways connected feature extraction analyzes data.

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Visualizing This Week in Tech

Learn how to visualize common elements amongst the barrage of weekly tech stories with knowledge graphs and machine learning techniques.

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AI & Graph Technology: What Are Knowledge Graphs?

Read the second installment of this blog series on artificial intelligence on the ways knowledge graphs add context for decision support.

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AI and Graph Technology: 4 Ways Graphs Add Context

Read the first installment of this blog series on artificial intelligence on the ways graph technology adds necessary context for powerful AI solutions.

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Toward AI Standards: Context Makes AI More Reliable and Trustworthy

Discover why native graph technology is the key to making artificial intelligence and machine learning more reliable and trustworthy.

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Graphs in Banking: Integration with AI & Machine Learning [Video]

Check out this webinar on graph technology within the financial services industry, featuring use cases on fraud detection, MDM and IAM.

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Toward AI Standards: Context Makes AI More Robust

Read this third blog in our series “Toward AI Standards” and discover how graph technology adds context to data relationships for more robust AI solutions.

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Deciphering Product DNA: Next-Level PDM with AI & Knowledge Graphs

Increasingly complex products undoubtedly require greater management of components, function and data. Classic product data management (PDM) has long reach its limits in this respect. Breaking down product DNA is now driven by artificial intelligence (AI) and knowledge graphs. In… Read more →

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Liberating Knowledge: Machine Learning Techniques with Neo4j

Explore how Hume leverages natural language understanding, graph analytics and AI capabilities to connect data and share knowledge.

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Toward AI Standards: Graph Technology for Responsible AI

Read the first installment of this four-part series on how graphs provide the context artificial intellingence needs to remain reliable and trustworthy.

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Graphs in Automotive & Manufacturing: Unlock New Value from Your Data [Video]

Check out this webinar on using graph database technology in the manufacturing and automotive industries, including the use of graph algorithms in AI.

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Toward AI Standards: Why Context Is Critical for Artificial Intelligence

Learn what Neo4j CEO Emil Eifrem believes is the most critical component of both technical and ethical standards for AI – and how we might make it happen.

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